Updated practice for review articles and position papers in ArXiv CS category (blog.arxiv.org)

Article summary

ArXiv's computer science category has updated its moderation practice for review articles and position papers, requiring them to be accepted at a journal or conference and complete successful peer review before being considered for submission. This change is due to the influx of low-quality submissions, partly attributed to the ease of generating content with large language models. The goal is to maintain the quality of content on ArXiv and ensure that valuable review articles and position papers are shared. This change does not affect the submission of other types of scientific papers.

Main themes

• ArXiv moderation policy
• Large language models
• Peer review process
• Scientific publishing
• Content quality control
• Academic integrity

What commenters say

• The new policy is necessary to prevent the flooding of low-quality review articles and position papers generated by large language models.
• Requiring peer review for review articles and position papers may disadvantage authors who aim for high-quality surveys in highly-ranked journals with long review times.
• The old editorial filter model is no longer effective in the digital age, and a new model based on reputation and community endorsement may be needed.
• ArXiv should use AI to accelerate the review process instead of banning AI-generated content.
• The policy change may not be effective in stopping the flood of low-quality submissions, as it relies on the integrity of peer review in journals and conferences.
• The distinction between human-generated and AI-generated content is not always clear, and the policy may inadvertently reject valuable contributions.
• The policy change is a step in the right direction, as it prioritizes the quality of content and maintains the integrity of scientific publishing.
• The use of AI in generating review articles and position papers raises concerns about the potential for misinformation and the need for more robust quality control measures.